RAG Production Engineeringv1.0.0

Build a production RAG system that ingests internal documents (PDFs, wikis, Slack exports) and answers employee questions with source citations. The pipeline must handle access controls, compliance requirements, and daily document updates while keeping latency under 3 seconds.

Implement a RAG system over legal statutes, case law, and firm memos to surface relevant precedents and clauses. The system uses sentence-window chunking with reranking to ensure precision, and must cite exact sources for attorney review.

Create a RAG pipeline that indexes product manuals, release notes, and support tickets, enabling a chatbot to answer customer queries accurately. The system monitors answer faithfulness and falls back gracefully when no relevant context is found.

Build a RAG system for healthcare professionals that retrieves relevant clinical guidelines and research papers. It uses parent-child chunking and reranking to balance precision and context, with strict latency and compliance constraints (HIPAA).

Deploy a RAG solution over SEC filings, earnings call transcripts, and analyst reports to answer complex financial questions. The architecture combines hybrid search and reranking, and supports multi-step reasoning via agentic RAG.

Offer a managed RAG-as-a-Service platform where customers upload their documents and query via API. Pricing is based on number of queries, document volume, and feature tiers (e.g., advanced retrieval, evaluation dashboard).

Provide expert consulting to design, implement, and optimize RAG pipelines for enterprises. Services include architecture assessment, chunking strategy tuning, evaluation framework setup, and production monitoring.

Release an open-source RAG framework (e.g., chunking library, eval toolkit) and monetize through a commercial edition that adds advanced security, access control, multi-tenancy, and observability. The free tier drives adoption, while enterprises pay for governance and support.